The goal of this paper is to evaluate the results of regional economic growth estimates at multiple spatial scales using spatial panel data models. The spatial scales examined are minimum comparable areas, micro-regions, meso-regions and states over the period between 1970 and 2000. Alternative spatial panel data models with fixed effects were systematically estimated across those spatial scales to demonstrate that the estimated coefficients change with the scale level. The results show that the conclusions obtained from growth regressions are dependent on the choice of spatial scale. First, club convergence hypothesis cannot be rejected suggesting there are differences in the convergence processes between the north and south in Brazil. Moreover, the positive average-years-of-schooling coefficient gets larger as more aggregate spatial scales are used. Transportation costs effect is positive and statistically significant to economic growth only at the state level. Population density coefficients show that higher populated areas are harmful to economic growth demonstrating somehow that congestion effects are operating at the MCA, micro-regional and meso-regional spatial scales, but their magnitudes vary across the geographic scales. Finally, the values of spatial spillovers coefficients also vary according to the spatial scale under analysis. In general, such coefficients are statistically significant at the MCA, micro-regional and meso-regional levels; but, at state level those coefficients are no longer statistically significant suggesting that spatial spillovers are bounded in space.